Use cases · Retention & Customer Value
Retention is a question of who returns, who lapses and what moves them. Ask it of a model trained on your own customers and the answer comes back as ranked plays: who to reach, with what, through which channel, and how to prove it worked.
KPIs, in priority order
lifetime_spend_label Move customers into higher bands, above all from Moderate to High. orders_label This use case Turn one-time buyers into repeat buyers. loyalty_engagement_label Grow the Engaged group, who spend twice as much and repeat three times as often. account_age_label See more customers reach Long-standing, five years or more. Channels
KPIs, in priority order
at_risk This use case Move subscribers from High churn risk to Low, above all ahead of renewal. is_cycler Turn subscribers who join for one release into year-round subscribers. 7d_adfrequency Keep ad load below the level where cancellations climb. Channels
KPIs, in priority order
renewal_risk This use case Move holders from High renewal risk to Low before renewal opens. events_attended_band Keep holders at the games: attendance predicts renewal. app_user Keep holders in the app, where ticket exchange stops empty seats becoming lost renewals. Channels
KPIs, in priority order
recency_tier This use case Win back Cooling guests before they lapse, and Lapsed regulars where they now live. frequency_tier Keep Regulars at their own cadence. rewards_member Keep members active between rewards. Channels
Every use case starts with a brief like this one.
An example run for Pacewright Running, a Neuralift demo brand: a performance running brand with its own shoes and apparel. Four of its seven ranked actions are retention plays: step through them and the map lights up the segments each one reaches.
lifetime_spend_labelorders_labelloyalty_engagement_labelaccount_age_label Shoebox Purists
Dana
Representative customer
10,031 customers · 12.4%
Run-Club Shoe Faithful
Marcus
Representative customer
9,747 customers · 12.0%
Comfort Stride Crowd
Linda
Representative customer
7,219 customers · 8.9%
Single-Lane Runners
Theo
Representative customer
4,882 customers · 6.0%
Promo-Timed Online Shoe Shoppers
Kayla
Representative customer
4,809 customers · 5.9%
Fashion-First Footwear Buyers
Tatum
Representative customer
3,788 customers · 4.7%
Full-Price Road Regulars
Owen
Representative customer
3,566 customers · 4.4%
Tennis Court Regulars
Victor
Representative customer
3,562 customers · 4.4%
Style-First Sneaker Buyers
Jade
Representative customer
3,400 customers · 4.2%
New Year Speed Seekers
Priya
Representative customer
3,307 customers · 4.1%
Counter-Fit Running Households
Rosa
Representative customer
3,146 customers · 3.9%
Clearance-Rack Shoe Hunters
Derek
Representative customer
2,994 customers · 3.7%
Trailhead Newcomers
Wyatt
Representative customer
2,889 customers · 3.6%
Pitch-and-Court Rookies
Mateo
Representative customer
2,854 customers · 3.5%
Accessory-Led Store Visitors
Joan
Representative customer
2,737 customers · 3.4%
Warm-Month Running Purists
Nina
Representative customer
2,654 customers · 3.3%
Opt-Out Footwear Loyalists
Harold
Representative customer
2,554 customers · 3.1%
Shoes-Only Full-Price Shoppers
Celia
Representative customer
2,491 customers · 3.1%
Court Sport Starters
Andre
Representative customer
2,383 customers · 2.9%
December Running Newcomers
Sienna
Representative customer
2,125 customers · 2.6%
One more pair moves them up a band
$130their typical lifetime spend today $200where the High band starts
Signed-in members spend twice as much
$325engaged members $156everyone else
They buy models fresh to market
12 momedian time past launch of the freshest model they bought
The store already wins repeat orders
57%of these households buy again 31%brand-wide
An example run for VistaStream, a Neuralift demo brand: a US streamer with ad-supported and ad-free plans, briefed to keep subscribers past renewal. Four of its seven ranked actions are retention plays: step through them and the map lights up the segments each one reaches.
7d_adfrequencyat_riskis_cycler Weekend Family Co-Viewers
Maya
Representative customer
512,000 subscribers · 12.2%
Premium Ad-Free Loyalists
Clive
Representative customer
452,000 subscribers · 10.8%
Live Sports Ad-Tier Viewers
Cody
Representative customer
438,000 subscribers · 10.4%
Prestige Drama Bingers
Harper
Representative customer
396,000 subscribers · 9.4%
Release-Window Cyclers
Eli
Representative customer
382,000 subscribers · 9.1%
Daytime Reality Streamers
Bev
Representative customer
344,000 subscribers · 8.2%
Kids' Profile Households
Gemma
Representative customer
298,000 subscribers · 7.1%
Mobile Commuter Snackers
Noor
Representative customer
276,000 subscribers · 6.6%
Spanish-Language Viewers
Lucia
Representative customer
236,000 subscribers · 5.6%
Ad-Fatigued Late-Night Viewers
Hal
Representative customer
214,000 subscribers · 5.1%
Price-Sensitive Downgraders
Brent
Representative customer
188,000 subscribers · 4.5%
Documentary Deep-Divers
Rhys
Representative customer
168,000 subscribers · 4.0%
Movie Night Renters
Jules
Representative customer
154,000 subscribers · 3.7%
Returning Trialists
Ari
Representative customer
142,000 subscribers · 3.4%
Cyclers leave within weeks of a finale
71%cancel within 30 days of a finale 18%everyone else
Cancellations climb past 120 ads a week
3.1×cancel rate above 120 ads 1×under 60 ads
They cycle out after the final game
48%cycle out between seasons
A light first month keeps them
2.2×retention under 40 ads a week 1×at the ad-tier average
An example run for Granite Pulse Arena, a Neuralift demo brand, briefed to renew more season holders. Four of its seven ranked actions are retention plays: step through them and the map lights up the segments each one reaches.
events_attended_bandapp_useravg_event_spendparking_userrenewal_riskpartner_optin Concert-Only Ticket Buyers
Lola
Representative customer
14,600 fans · 13.8%
Single-Game Family Outings
Paige
Representative customer
12,300 fans · 11.6%
App-Active Game-Day Regulars
Jamal
Representative customer
10,900 fans · 10.3%
Season Ticket Core
Gus
Representative customer
9,200 fans · 8.7%
Student Night Crowd
Zack
Representative customer
8,900 fans · 8.4%
Late-Arriving Downtown Workers
Ravi
Representative customer
8,400 fans · 7.9%
Merch-First Fans
Tess
Representative customer
7,600 fans · 7.2%
Lapsed Season Holders
Doug
Representative customer
6,800 fans · 6.4%
Resale-Market Opportunists
Nico
Representative customer
6,100 fans · 5.8%
Parking-Pass Early Arrivers
Carla
Representative customer
5,200 fans · 4.9%
Out-of-Town Visiting Fans
Hugh
Representative customer
4,700 fans · 4.4%
Kids Club Members
Abby
Representative customer
4,400 fans · 4.2%
Premium Club Seat Holders
Vivian
Representative customer
3,900 fans · 3.7%
Corporate Hospitality Guests
Elaine
Representative customer
2,900 fans · 2.7%
Empty seats predict a lost renewal
3.4×non-renewal after missing half the last ten games 1×holders at most games
They never stopped coming to the big games
3.1games a season since giving up seats 1.2other single-game buyers
Students who come five times keep coming
48%of 5+ game students buy the next year 12%other students
Kids' club families come as four
3.6tickets per visit 2.1everyone else
An example run for Leo's Steakhouse, a Neuralift demo brand with 24 restaurants, briefed to keep regulars coming back. Four of its seven ranked actions are retention plays: step through them and the map lights up the segments each one reaches.
aov_tierfrequency_tierrecency_tierrewards_member Celebration Diners
Bella
Representative customer
18,600 guests · 12.4%
Business Lunch Regulars
Grant
Representative customer
16,200 guests · 10.8%
Happy-Hour Bar Grazers
Kim
Representative customer
15,800 guests · 10.6%
Discount-Led Occasionals
Rick
Representative customer
14,900 guests · 10.0%
Family Sunday Diners
Paul
Representative customer
13,600 guests · 9.1%
Lapsed Weekend Regulars
Lynn
Representative customer
11,200 guests · 7.5%
Takeout Steak Night Households
Ben
Representative customer
10,300 guests · 6.9%
Loyalty Points Maximisers
Shane
Representative customer
9,900 guests · 6.6%
Wine-Led Premium Diners
Olivia
Representative customer
9,400 guests · 6.3%
Pre-Theatre Set-Menu Guests
Ivy
Representative customer
8,700 guests · 5.8%
First-Visit Tourists
Ellie
Representative customer
7,100 guests · 4.8%
Bar-to-Dining Upgraders
Rafael
Representative customer
5,600 guests · 3.7%
Gift-Card Redeemers
Nell
Representative customer
4,300 guests · 2.9%
Private Dining Bookers
Diane
Representative customer
3,800 guests · 2.5%
Most now live nearer the new Riverside location
68%within 15 minutes of Riverside 21%everyone else
One missed visit is the warning
3×lapse rate after a missed usual visit 1×regulars on cadence
Most never come back after the card
14%return within a year 61%first-time guests who paid
Their next occasion is already on the calendar
11 momedian gap between celebration visits
A churn model hands every customer a number: who might leave. It doesn't say why, what would keep them, or which of them were never really leaving. Neuralift finds the groups behind the score, the reason each one is drifting, and the play that brings it back.
A churn score
A Neuralift view
Inside the top churn decile
Spend retention budget on the customers who'd leave without it, not on the ones who'd stay anyway or were never coming back.
Each group comes with why it's drifting, so the play fits: a replacement prompt, a fit service, a store visit, rather than one discount for everyone.
Every play ships with a holdout, so you can show the customers you kept that you'd otherwise have lost.
A churn model hands every customer a number: who might leave. It doesn't say why, what would keep them, or which of them were never really leaving. Neuralift finds the groups behind the score, the reason each one is drifting, and the play that brings it back.
A churn score
A Neuralift view
Inside the top churn decile
Spend retention budget on the customers who'd leave without it, not on the ones who'd stay anyway or were never coming back.
Each group comes with why it's drifting, so the play fits: a replacement prompt, a fit service, a store visit, rather than one discount for everyone.
Every play ships with a holdout, so you can show the customers you kept that you'd otherwise have lost.
A churn model hands every customer a number: who might leave. It doesn't say why, what would keep them, or which of them were never really leaving. Neuralift finds the groups behind the score, the reason each one is drifting, and the play that brings it back.
A renewal score
A Neuralift view
Inside the top renewal-risk decile
Spend retention budget on the customers who'd leave without it, not on the ones who'd stay anyway or were never coming back.
Each group comes with why it's drifting, so the play fits: a replacement prompt, a fit service, a store visit, rather than one discount for everyone.
Every play ships with a holdout, so you can show the customers you kept that you'd otherwise have lost.
A churn model hands every customer a number: who might leave. It doesn't say why, what would keep them, or which of them were never really leaving. Neuralift finds the groups behind the score, the reason each one is drifting, and the play that brings it back.
A churn score
A Neuralift view
Inside the top churn decile
Spend retention budget on the customers who'd leave without it, not on the ones who'd stay anyway or were never coming back.
Each group comes with why it's drifting, so the play fits: a replacement prompt, a fit service, a store visit, rather than one discount for everyone.
Every play ships with a holdout, so you can show the customers you kept that you'd otherwise have lost.
Neuralift builds a model of your customers around your bespoke use case. Explore more use cases through the lens of our demo brands, their KPIs, and actions.
Pacewright Running 7 ranked actions 
Copper Cactus Casino 9 ranked actions 
Leo's Steakhouse 8 ranked actions 
Granite Pulse Arena 8 ranked actions 
Nordvale Gaming 9 ranked actions 
VistaStream 8 ranked actions Stories, papers and the events where we meet retention, CRM and loyalty teams.
Case study Sep 22, 2026 Delaware North finds the customers legacy segmentation couldn't see Read the story 
White paper Sep 15, 2026 From warehouse to winning Read the paper 
White paper Jul 2, 2026 From customers to superfans with AI-native segmentation discovery Read the paper 
Event Jun 1, 2026 CRMC 2026 See the event Sixteen CMOs had a CDP. One liked it. Blog Jan 7, 2025 You have a CDP. So what?! Read Our team is always happy to talk through your customer data challenges and opportunities. We usually respond within a day, and we love helping teams see what their customer data can tell them.